A DSPN modeling and simlation Tool for Avionics System

AbstractAvionics System is the typical real-time embedded system and DSPN-base system evaluation is the important theoretical basis and supporting technology of the development of it. This paper focuses on the design of the tool based on DSPN, called Aero_DSPN, with the functions of component modelling and simulation analysis of the avionics system, to offer invaluable process and organizational design support. We illustrate system modelling and simulation analysis in a case study of avionics system

Software Reliability Growth Model with Partial Differential Equation for Various Debugging Processes

Most Software Reliability Growth Models (SRGMs) based on the Nonhomogeneous Poisson Process (NHPP) generally assume perfect or imperfect debugging. However, environmental factors introduce great uncertainty for SRGMs in the development and testing phase. We propose a novel NHPP model based on partial differential equation (PDE), to quantify the uncertainties associated with perfect or imperfect debugging process. We represent the environmental uncertainties collectively as a noise of arbitrary correlation. Under the new stochastic framework, one could compute the full statistical information of the debugging process, for example, its probabilistic density function (PDF). Through a number of comparisons with historical data and existing methods, such as the classic NHPP model, the proposed model exhibits a closer fitting to observation. In addition to conventional focus on the mean value of fault detection, the newly derived full statistical information could further help software developers make decisions on system maintenance and risk assessment

Comparation of differences in the performance of corporate social responsibility between Chinese and American pharmaceutical enterprises—based on corporate social responsibility report

Objective: We compared Chinese and American pharmaceutical companies’ corporate social responsibility (CSR) reports to determine their differences and to analyze the possible reasons for them.Methods: We took as a model the top 500 pharmaceutical companies from Torreya’s (a global investment bank) list of the 1,000 most valuable pharmaceutical companies in the world. We then collected the 2020 corporate social responsibility reports of 97 Chinese and 94 American pharmaceutical companies. These reports were analyzed using software such as ROST Content Mining 6.0 and Gephi 0.92.Results: We formed a high-frequency word list, a semantic network diagram, and a high-frequency word centrality scale for the Chinese and American pharmaceutical corporate social responsibility reports. The Chinese pharmaceutical companies’ corporate social responsibility reports formed a layout of “double centers and double themes,” and the text paid more attention to the disclosure of environmental protection information. The American pharmaceutical companies formed a report presentation form of “three centers and two themes,” focusing on corporate social responsibility information disclosures from the perspective of humanistic care.Discussion: The differences in between Chinese and American pharmaceutical companies’ corporate social responsibility reports may be due to different corporate development strategies, regulatory requirements, social demands, and the concept of “corporate citizenship.” This study makes recommendations for Chinese pharmaceutical companies to better fulfill their CSR at three levels: policy-making, company management, and society

Effects of nitrogen application on seed yield, dry matter and nitrogen accumulation of Siberian wildrye (Elymus sibiricus L.)

Siberian wildrye (Elymus sibiricus L.) is a perennial and self-fertilizing forage grass that support animal husbandry and environmental sustenance in the world. In order to explore influence of nitrogen(N) application in Siberian wildrye seed production, the field experiments were conducted to evaluated the effect of different N treatments (of 0, 30, 60, 90 and 120 kg/hm2) on dry matter, N accumulation, transport and utilization, yield components and seed yield of Siberian wildrye DJ-01, which was generated and stored in our lab. The results showed that the 90 kg/hm2 group significantly improved Fertile tillers m−2, spikelets per fertile tiller, 1000-grain weight and seed yield. Furthermore, the seed yield of 90 kg/hm2 group reached 899.3 kg/hm2 and elevated 45.6% compared with 0(CK) group. Moreover, we found that Siberian wildrye exhibited more advantages in dry matter and N translocation. The increment of grain N depended on pre-anthesis dry matter translocation (Pre-DMT) and pre-anthesis N translocation (Pre-NT), but not post-anthesis dry matter accumulation (Post-DMA) and post-anthesis N uptake (Post-NU) to seed yield. With the increase of N, N partial productivity and N absorption efficiency gradually decreased. All data showed the 90 kg/hm2 had the best effects on seed yield components, seed yield, dry matter accumulation (DMA), N accumulation and N efficiency. These results provide an ideal strategy to expand the plant area of Siberian wildrye

Type I CRISPR-Cas-mediated microbial gene editing and regulation

There are six major types of CRISPR-Cas systems that provide adaptive immunity in bacteria and archaea against invasive genetic elements. The discovery of CRISPR-Cas systems has revolutionized the field of genetics in many organisms. In the past few years, exploitations of the most abundant class 1 type I CRISPR-Cas systems have revealed their great potential and distinct advantages to achieve gene editing and regulation in diverse microorganisms in spite of their complicated structures. The widespread and diversified type I CRISPR-Cas systems are becoming increasingly attractive for the development of new biotechnological tools, especially in genetically recalcitrant microbial strains. In this review article, we comprehensively summarize recent advancements in microbial gene editing and regulation by utilizing type I CRISPR-Cas systems. Importantly, to expand the microbial host range of type I CRISPR-Cas-based applications, these structurally complicated systems have been improved as transferable gene-editing tools with efficient delivery methods for stable expression of CRISPR-Cas elements, as well as convenient gene-regulation tools with the prevention of DNA cleavage by obviating deletion or mutation of the Cas3 nuclease. We envision that type I CRISPR-Cas systems will largely expand the biotechnological toolbox for microbes with medical, environmental and industrial importance

Sulfated Modification and Bioactivity Analysis of Polysaccharide from Porphyra

The polysaccharides were obtained by microwave-assisted enzymatic extraction from Porphyra, and then modified by sulphate method. Single factor and orthogonal experiments were used to optimize the sulfated modification process of polysaccharides, which were identified by Fourier transform infrared spectroscopy (FT-IR). The antioxidant and hypoglycemic activity changes of the polysaccharides modified by sulphate and chlorosulfonic acid-pyridine method were also studied. Results showed that the optimal technology parameters were the ratio of solid to liquid 1:80 g/mL, the mass ratio of Porphyra polysaccharide to ammonium sulfate 10:9 g/g, reaction time 33 min, and the maximum degree of substitution was 2.94. FT-IR showed that the characteristic absorption peaks of sulfate radical group appeared near 801 and 1123 cm−1, and the possible substitution position of sulfate radical group was C-6. The sulfate modification could significantly improve the scavenging ability of DPPH, O2− and OH free radicals and the inhibitory effect on α-glucosidase activity of the polysaccharides (P<0.05). The antioxidant and hypoglycemic activity of the polysaccharides modified by sulphate method were both higher than that by chlorosulfonic acid-pyridine method (P<0.05), indicating that sulphate method was applicable to modify the Porphyra polysaccharide. This study provides a theoretical basis for the further development of polysaccharides from Porphyra as a functional food

Jasmine (Jasminum grandiflorum) Flower Extracts Ameliorate Tetradecanoylphorbol Acetate Induced Ear Edema in Mice

Published data from in vitro assays support the anti-inflammatory effects of jasmine (Jasminum grandiflorum Linn.) but limited studies are reported in animal models. Herein, the anti-inflammatory effects of jasmine flower extracts (JFEs) including ethanol extract (JF-EE), petroleum ether extract (JF-PEE), ethyl acetate extract (JF-EAE), and n-butanol extract (JF-BE) were evaluated in a mouse ear edema model. Acute mouse ear skin inflammation was induced by tetradecanoylphorbol acetate (TPA; 125 µg/mL) and then treated with JFEs (100 mg/mL) or dexamethasone (DEX; 6.25 mg/mL; as a positive control). Jasmine flower extracts alleviated ear edema by reducing TPA-increased ear thickness and ear weight by 30.8% to 64.1% and 24.0% to 47.1%, respectively, whereas DEX showed comparable activity (by 71.8% and 49.1%, respectively). Their anti-inflammatory effects were supported by data from the immunohistochemical assays. Jasmine flower extracts reduced the inflammatory cells (from 5.5- to 9.5-fold) and the expressions of inflammation related enzymes including cyclooxygenase-2 and inhibitor of kappa-B kinase (from 1.9- to 2.8-fold and from 7.1- to 11.0-fold, respectively). Findings from this study showed that JFEs were able to ameliorate TPA-induced mouse skin inflammation. However, future studies on the underlying mechanisms of jasmine flower’s anti-inflammatory effects are warranted

DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization

Visual reinforcement learning (RL) has shown promise in continuous control tasks. Despite its progress, current algorithms are still unsatisfactory in virtually every aspect of the performance such as sample efficiency, asymptotic performance, and their robustness to the choice of random seeds. In this paper, we identify a major shortcoming in existing visual RL methods that is the agents often exhibit sustained inactivity during early training, thereby limiting their ability to explore effectively. Expanding upon this crucial observation, we additionally unveil a significant correlation between the agents' inclination towards motorically inactive exploration and the absence of neuronal activity within their policy networks. To quantify this inactivity, we adopt dormant ratio as a metric to measure inactivity in the RL agent's network. Empirically, we also recognize that the dormant ratio can act as a standalone indicator of an agent's activity level, regardless of the received reward signals. Leveraging the aforementioned insights, we introduce DrM, a method that uses three core mechanisms to guide agents' exploration-exploitation trade-offs by actively minimizing the dormant ratio. Experiments demonstrate that DrM achieves significant improvements in sample efficiency and asymptotic performance with no broken seeds (76 seeds in total) across three continuous control benchmark environments, including DeepMind Control Suite, MetaWorld, and Adroit. Most importantly, DrM is the first model-free algorithm that consistently solves tasks in both the Dog and Manipulator domains from the DeepMind Control Suite as well as three dexterous hand manipulation tasks without demonstrations in Adroit, all based on pixel observations